Evidence from the fossil record shows that gluttonous insect-eating shrew didn’t live where a species distribution technique drawn by biologists put it 20,000 years ago to survive the reach of glaciers, says University of Oregon geologist Edward B. Davis. The shrew is not alone.

According to a new study by Davis and colleagues, fossil records of five ancient mammalian species that survived North America’s last glacial period point to weaknesses in the use of ecological niche models and hindcasting to predict future animal and plant habitats. As a result, Davis says, the modeling needs to be fine-tuned for complexities that might be harvested from fossils.

Ecological niches use modern habitat distributions and climate; hindcasting adds predictive power by adding major past climate shifts into the models. That modeling combination — as seen in a 2007 study led by Eric Waltari, then of the American Museum of Natural History in New York — had the short-tailed shrew surviving the last ice age in mostly Texas and the Deep South. Conclusions drawn in other studies, Davis noted in the new study, also are biased toward southern locations for ice-age surviving mammals of the Pleistocene Epoch.

Short-tailed shrew, according to fossil records, did not live in the predicted ranges. Instead they lived across north central and northeast United States, closer to the glaciers and where they are widely found today.

“It’s almost as though it is living in all of the places that the model says it shouldn’t be living in and not in any of the places that the model says it should be living in,” said Davis, who also is manager of the paleontological collection at the UO Museum of Natural and Cultural History. “This suggests to me that whatever the model is keying on is not actually important to the shrew.”

Nor to the American marten, two species of flying squirrels and the Gapper’s red-backed vole, all of which lived mostly outside of predicted ranges, according to the fossil record. Northern and southern flying squirrels, the Davis study found, shared a compressed geographic region. It may be, Davis said, that some species tolerate competition under harsh conditions but separate when abundant resources are available.

Davis noted that an important but under-cited 2010 paper on rodents by Robert Guralnick of the University of Colorado and Peter B. Pearman of the Swiss Federal Research Institute also showed problems with hindcast projections. Those for lowland rodents in the last ice age did not hold up, but those for a higher elevation species did.

“Our findings say that we need to pay more attention to the potential problems we have with some of our modern methods, and the way that we can improve our understanding of how species interact with the environment,” said Davis, who added that his study was inspired by Waltari’s. “The way to improve our forecasting is to include data from the fossil record. It can give us more information about the environments that species have lived in and could live in.”

The findings appear in the November issue of the journal Ecography. In a special section of the journal, the Davis paper is packaged with four papers on research initially presented in a symposium on conservation paleobiogeography in 2013 at a biennial meeting of the International Biography Society. The Davis paper is co-authored by Jenny L. McGuire, now at Georgia Tech University, and former UO doctoral student John D. Orcutt, who is now at Cornell College in Iowa.

Davis and McGuire co-hosted the symposium, edited the special issue and penned an editorial that accompanies the five papers. Conservation paleobiogeography, Davis said, “is the idea that we can help people understand questions that arise from conservation needs using data from the fossil record.” Doing so, he said, may explain how species shift their ecological roles, or evolve, to survive amid abrupt changes in their habitats.

“Our paper raises questions about some of the work on projecting future ranges of mammals, and we suggest some directions forward,” Davis said. “We have concerns about the precision of the modeling techniques now being used. We don’t have any concerns about climate change happening and that it going to cause geographic range shifts for mammals and plants. The thing I want to do, as a scientist, is to have the best models possible so as we’re making informed decisions as a society.”

Or admitting in memoirs as Gus Speth does here http://community-wealth.org/content/angels-river that all the environmental hyping is really just an excuse for collectivist economic and social transformations.
Uncle Karl, unfortunately, remains a lodestar for too many in their 21st century visions for all of us. Since we would decline, we get these created ‘catastrophe’ myths to force the vision anyway.

This is more in response to Duster – One should never confuse a degree with education. how a person earns a living may be degree oriented, but his brain, intellect, and thinking are not necessarily limited to that singular field. If that were the case – a degree was the only thing that sat your career field – there wouldn’t be any “climate scientists” to speak of.

Or perhaps mammals are much more adaptive than they thought. After all, a near hairless semi-aquatic primate living in equatorial swamps, lagoons and coastal waters adapted to live in Arctic lands beset by year round snows, hot and cold deserts, .lush forests, grassy steppes, below sea level, villages, cities and even managed to survive in vacuums.

Indeed a good point. Though humans have of course in culture a way to speed up adaptation considerably. Nevertheless hindcasting to predict the future will never be working in Living systems. Read the philosopher Bergson (Creative Evolution) to understand why (and read him carefully don’t look at what others have to say about him or put him under vitalism). The rule about hindcasting is also true for Clmate science as it is not really a closed system that is observed.

So did the shrew evolve to cope with the habitat as it changed? That would mean it wouldn’t need to move and follow the ecosystem.
It’s hard to tell from a fossil if the behaviour or genes have changed.
So does the model assume the species is constant? That would seem like a big assumption but hard to see how it can hind cast without it.

It probably adapted. Evolved means creating a new species, adapting is favoring certain traits which allow for better survivability in new circumstances.
There is also the possibility that the shrew did neither, already being able to handle both warm and cold conditions, much like my chickens which can live.in 100 degree heat and in winter survive in 10 degrees.

Evolution is a form of adaptation. Adaptation consists of a combination of three primary “tactics”: acclimatization, development (fetal and post-natal), and evolutionary changes (a selective filter). With humans we toss in cultural adaptation (mainly technological). Migration can be a form of adaptation, but leads to conflict with residents in new territory that are already well placed and outnumber the intruding population. Short lived species like fruit flies and mayflies mainly adapt through selective (evolutionary) means. Longer lived species have to depend more on acclimatization and developmental adaptation for survival. The shifts in red-blood cell production seen in human populations living at high altitudes are a combination of developmental and acclimatization adaptation.
Speciation is the cumulative result of selective (evolutionary) changes.

“It’s almost as though it is living in all of the places that the model says it shouldn’t be living in and not in any of the places that the model says it should be living in,”
The model says exactly what it was told to say. GIGO

Sigh. Another case of unnecessary ”me too”-research in Climate Science™. Everybody who has ever worked seriously with Pleistocene fossils knows this phenomenon perfectly well, it is known as “disharmonious faunas”, i. e. animals whose “ecological niches” don’t overlap today occur together. Classical examples are e. g. Lions and Caribou, Hyaenas and Muskox or Ptarmigan and Partridges.
There is three main reasons for this:
1. There are “extinct climates”, i. e. during ice-ages many areas had climates that do not occur anywhere on Earth today, and in these areas animals and plants occurred in combinations that do not occur anywhere today either.
2. The current “ecological niches” of animals often (=usually) do not cover their entire potential climatic range. For large animals this is often because they have been exterminated in (often large) parts of their natural range. Animals are also very often prevented from dispersing over their entire potential range by geographical barriers of various kinds (rivers, straits, forests, grasslands, mountains etc).
3. “Ecological niches” evolve like everything else. An animal species may be osteologically identical to a form that lived during the LGM 20,000 years ago, but its behaviour and ecological tolerance may well have changed.
By the way, floras work just the same. There were “disharmonious forests” too, e. g. much of south-central US was dominated by spruce-elm/oak forests, a combination that hardly occurs anywhere today, while much of Eurasia was “mammoth-steppe” a a dry treeless habitat with a (for us) weird mixture of southern sunlight-loving plants and arctic tundra species that never occur together nowadays. The low glacial CO2 levels were probably important for the composition of floras by making plants (particularly C3 species) much more susceptible to drought.
By the way, I completely and wholeheartedly agree that it is necessary to use both the fossil and the historical record to understand animal distribution. In contrast to what many “ecologists” seem to believe nothing is ever static or stable in nature, particularly not in the glaciation-dominated icehouse climate we are living in.

“The current “ecological niches” of animals often (=usually) do not cover their entire potential climatic range”
This is a very good point. People assume Lions are a tropical species because they currently are only found in the wild in sub Saharan Africa and India but we know from the fossil record that in the past they were native in climatic zones from Siberia and the Yukon to Peru. Moreover any zoo keeper will tell you that Lions do very well in cold climates at temperatures well below freezing.

Illuminating – good to get the real biology / ecology perspective.
I saw in a recent documentary that much of north America had a rich ecosystem with abundant megafauna for the early part of the last glaciation. However the final 20k years or so when the glaciation intensified devastated this ecosystem and caused a number of extinctions. Maybe low CO2 also contributed to this baleful climate just prior to the Holocene.
Could increasing CO2 cause reforestation of some grasslands?

“At the very least, the Last Glacial Maximum compressed climatic zones and reduced the areas of biomes, including those now extinct”
It’s not that simple. Ice-ages don’t simply “compress climatic zones”. Desert and steppe areas are much larger during ice-ages. Forest areas mostly shrink and move.

PS I might add that using modern ranges to study conditions/distributions in the past do work fairly well for interglacial periods which had reasonably similar climate to the present one.
However this does not do much good in North America where Pleistocene chronology still isn’t good enough to consistently identify interglacials before the last one (Sangamonian).

Good comments. pretty much says all that needs to be said.
But I’m surprised that “using modern ranges to study conditions/distributions in the past do work fairly well for interglacial periods which had reasonably similar climate to the present one.”
A major river changing its course would have huge impacts… and over those timescales they must have, surely?

@ tty – but does insisting on historical accuracy miss the point ? Modern ranges have to be the ideal ones because as we all know The Earth had a perfect climate until humans started to mess with it. Isn’t the preservation/restoration of that perfect climate what CAGW is all about ?

…As a result, Davis says, the modeling needs to be fine-tuned for complexities that might be harvested from fossils….
What nonsense! Everybody knows, in post-modern science, that the observations have got to be adjusted to fit with the models…

Good point.
Also, if we change the time scale of their models and run it backwards we will see, with certainty, that the little varmints will be established throughout a more northern range in the future.
Pick a random northern local, and when one of the little varmints shows up then we will have pinned down the exact day of the end of the current ice age.
Subsequent warming will then be irrefutable proof of AGW.

i think a mistake that a lot of these studies make is assuming that a plant/animal can only survive in one limited climate range. what if temperature changes and the plant/animal in question just keeps on keeping on? i dont think their vaunted models take that into account

Short-tailed shrew, according to fossil records, did not live in the predicted ranges. Instead they lived across north central and northeast United States, closer to the glaciers and where they are widely found today.
—————
A very basic fact, as far as I can tell, apart from the assumtion about the glaciers at that time.
I find it hilarious, as that not been the first or the last facts and data related to climate imposing a view of climate change and Long term Atmospheric functioning to be cyclic, and the Climatology still failing (extremely stubborn) to consider this as a possibility.
The simplest explanation of that above fact without the need of weird acrobatic performances will be that the climate 20K years ago was similar (for not saying very similar) to the Present day climate.
And if that so than 20K years ago the climate would have been at the end of the previous Interglacial and very close to the begining of the last Ice Age, which may mean also that at present we are at a similar point.
No Ice Age then yet.
The failure of the ecological niche models most probably is due to the assumption ( intellectual and scientific one though) that the last Ice Age was some 100K years long. In a cyclic climate (approach and consideration) that not possible according to the data.
The actual Holocene data suggest and point out that if climate been cyclic then the basic fundamental length of that cycle could not be longer by much than 20K years and most probably very very close to that mark, give or take a half millennium at most.
To me this is another call pressing for a need to consider the possibility of the climate been cyclic.
cheers

Glacial extent is not an assumption. Geological investigation clearly shows the extent of glaciers and ice sheets for the last glaciation and for those larger than it. Ice and sediment cores and other paleo proxies show the previous glacial cycles. Their dates are well constrained. While interglacials vary in duration by a factor of three or more, glacials are more regular, at around 100,000 years for the past million years or so, but shorter before that time.

@sturgishooper
November 19, 2014 at 10:19 am
Before we can debate anything about The Ice Age (or the last glacial period), can you explain what you mean by “glacial cycles”(seems like you refering to ice ages periodic successions), as I fail to see the point, ……and would you not accept that any paleoclimate period referred to is an estimation of the climate at that period according to paleoclimate data we have, where the estimation itself, or investigation as you call it has a chance of been considered an assumption?
So what you also saying is that you put your faith blindly at an estimation, and not considering at all a simple explanation of a fact which you do not accept as possible because of a close to a 100% certainty that the intelectual and scientific guess of the length of the Ice Age (the last glacial period) is unquestionable.
Any thing else you do know that will debunk that simple explanation mentioned, apart from the expected certainty of the length of the Ice Age (which actually is an estimation)?
As for constrained dates in Climatology, I would say that we already should have been constrained in a Run Away GW by now……. and the “climate scientist” still to busy on correcting and adjasting climate data of the last 50 years……..which puts the climatologic investigation ability to a very poor degree indeed, as far as I can tell.
Is very difficult for me to accept same geographical life patterns of animals for two very different climate periods, ……..any other kind of explanation will require, as I said early, very weird acrobatics, or put it simply, extreme spinning.
thanks for the comment…..looking forward for your next reply.
cheers

The merest glance at a chart of Pleistocene glaciations should make what I mean clear. I used standard geologic terminology. I can’t help it if you have never studied the Pleistocene glaciations.
A glaciation refers to the formation of extensive ice sheets in North America and Eurasia, plus more extensive montane glaciation in the SH, with a thicker and more extensive Antarctic ice sheet. During interglacials such as now, the Greenland Ice Sheet is a remnant of the huge sheets which form during glaciations.
“Ice Age” can mean different things. It’s usually obvious from context. At longer time frames, it shades into the term “Ice House”. At shorter, it can mean the entire Quaternary Period (Pleistocene and Holocene) or, although this is not preferred, one of the dozens of NH glaciations during that period. The cooling cycle of c. AD 1400 to 1850 is called the Little Ice Age because ice sheets didn’t develop, but montane glaciers grew.
The extent of the Wisconsin ice sheet in NA, for instance, is not an estimation. Its extent can be detected by observation. Climate around it can also be determined through analyses of such indicators as pollen and insects. In come cases paleo soils are preserved.
If you want to learn more, I suggest you read any text on the subject.

@ sturgishooper
November 19, 2014 at 1:27 pm
I used standard geologic terminology.
———–
Is this a standart geological terminology; “glacial cycles”?
That is what I was asking about….. and forgive me for not being able to see any explanation about that term given by you yet.
I also see that we refer to the term Ice Age differently. In my way Ice Age means colloqually the last glacial period, the one that was in question.
In that meaning Ice Age is same as a glacial period not as same as “ice ages”. There is Interglacials and glacial periods during an “ice age” but not so during a glacial period or the Ice Age (the last glacial period)
Is in capital leters as it is unique in meaning, only refers to one single glacial period the last one, the one that ended at circa 15K years ago.
Its length is not an unquestionable fact, is an estimation, and is bound to be tested by facts like the one highlighted in this above article.
A way to portray (dramatically) the above point will be in the lines:
“You can’t have a New York (or Toronto) alive as in present time (or similar to) in the Ice Age, is not possible. If there a similar New York in another period that period highly doubted to be the Ice Age or in (side) the Ice Age or in a glacial period.
New York as at present and a glacial period don’t put and can’t put together,……. and that is in human terms impossible, let alone in “rabbits” or any other inferior life creature adaptation terms”
Any way that is my take.
You are not the first to suggest me that I read more, and I appreciate your advice, but if you see, my point was on the how could one explain the same life geographical pattern found in two very different climate periods.
What do you suggest I read in that matter or subject?
Thanks for your reply again…..no hard feeling what so ever.
cheers

Whiten
You are wrong to call into question the timescale of glaciations over the Pleistocene which as has been pointed out are well established.
However you are right in the sense that glacial periods were not uniform and stable but were subject to large variation and instability. They were even interrupted by “micro-interglacials” lasting only a century or so.
“Chaotic” is a better description than “cyclical”. Chaotic systems can look cyclical but this can be illusory. A chaotic system driven by a Lorenz attractor for instance can appear regularly cyclical for a while and then spontaneously switch to a stable plateau or a very different periodicity.
Overall the recent glacial period is best characterised as being chaotic but (weakly) periodically forced by the Milankovitch orbital cycles of precession, obliquity and eccentricity.

phlogiston
November 19, 2014 at 11:55 am
You are wrong to call into question the timescale of glaciations over the Pleistocene which as has been pointed out are well established.
—————————
You could be right yes, but considering the facts I think I can, and actually anybody can call to question the timescale of the last glaciation in the probability of it been wrong.
And this is not the only one….the other day we had an exchange in another fact tha brings to question the validity of the estimation of the last glacial’s length,,, and somehow I will expect many more adding as time flows.
You free to not doubt it, yes, but consider that Holocene climate estimation is a much better one and still showing problems with the accuracy of it been a proper one……..and there is many well established “things” in climatology that have turned to be no so well established after all, for not saying very poorly established.
Also very unquestionable “things” in climatology have turned to be rightly called to question and scrutiny.
Besides, what you say as below:
“micro-interglacials” lasting only a century or so.”
makes no any sense really, even in an extreme spinning of the reality.
Sorry for saying that but, but that how it looks to me. I assume that is a new term you have come up with and I have the right to invoke the famous “Propter nomen” in that case…:-)
My approach in principle to the meaning of “chaotic” is as it been not in the realm of knowledge, just a saying, don’t jump the gun in this one…:-)
When it comes to the Milankovich cycles, my take is that the force of such cycles is as you say weak, or even very weak on climate, while considering the Long term Atmospheric functioning as cyclic also.
The most effect is in the pattern of polar regions extreme behaviour during climate cycles.
I personally blame the wrong estimation of the length of a glacial period in the coupling of this two particular natural events ( Mil. cycles and polar extreme behaviour) as a means do interpret climate beyond the point of ~18K years ago. Even the last long warming trend between ~17K years to ~7K years ago seems to be overestimated by the weight of the extreme range (behaviour) of the polar regions climatic data.
Any way thanks for your reply. I hope you understand that I call to question the timescale of the last glaciation as matter of probability, based in facts that support in a way such a call.
cheers

Reblogged this on Daily Browse and commented:
“It’s almost as though it is living in all of the places that the model says it shouldn’t be living in and not in any of the places that the model says it should be living in,” said Davis, who also is manager of the paleontological collection at the UO Museum of Natural and Cultural History. “This suggests to me that whatever the model is keying on is not actually important to the shrew.”

Environments were different from now, but still worked for many species. Burrowing rodents might emerge from their nests later and go into hibernation sooner, but would have access to abundant insects during the shorter but more intense summer season. Compare with Arctic insect hatches now. So the mammals could fatten up as much in less time.
Same goes for tree-dwellers.

Abstract
Systematics and Biodiversity – Volume 8, Issue 1, 2010
Kathy J. Willis et al4 °C and beyond: what did this mean for biodiversity in the past?How do the predicted climatic changes (IPCC, 2007) for the next century compare in magnitude and rate to those that Earth has previously encountered? Are there comparable intervals of rapid rates of temperature change, sea-level rise and levels of atmospheric CO2 that can be used as analogues to assess possible biotic responses to future change? Or are we stepping into the great unknown? This perspective article focuses on intervals in time in the fossil record when atmospheric CO2 concentrations increased up to 1200 ppmv, temperatures in mid- to high-latitudes increased by greater than 4 °C within 60 years, and sea levels rose by up to 3 m higher than present. For these intervals in time, case studies of past biotic responses are presented to demonstrate the scale and impact of the magnitude and rate of such climate changes on biodiversity. We argue that although the underlying mechanisms responsible for these past changes in climate were very different (i.e. natural processes rather than anthropogenic), the rates and magnitude of climate change are similar to those predicted for the future and therefore potentially relevant to understanding future biotic response. What emerges from these past records is evidence for rapid community turnover, migrations, development of novel ecosystems and thresholds from one stable ecosystem state to another, but there is very little evidence for broad-scale extinctions due to a warming world. Based on this evidence from the fossil record, we make four recommendations for future climate-change integrated conservation strategies.
DOI: 10.1080/14772000903495833http://www.tandfonline.com/doi/abs/10.1080/14772000903495833

The premise that these researchers are relying on; that mammals couldn’t possibly have not adapted to climate change in the manner assumed by the modelers; who are of course among the smartest of all mammals, and therefore understand how to adapt to climate. Really ?? they (we) know how to adapt to climate.
Well that premise is just one in a genre of similar creations of the mind of man.
Other examples. The Egyptians couldn’t possibly have built the pyramids; Mayans neither.
Ancient astronomers, couldn’t have figured out how the solar system works; much too complex.
Of course none of those ancient civilizations had T&V, or Monday/Thursday/Saturday/Sunday night football. Nor did they have a host of pocket finger toys to while away the day and take selfies of the pyramids which ancient aliens built while drawing all over the plains of Nazca.
So when the sun went down, they had nothing to do and nothing to see, so they all went to sleep.
So why is it that humans think their primitive model concepts are superior to what the whole damn system self organizes itself for its optimum performance.
I have watched videos of wild Asian crows figuring out a multistep sequence of how to get a food morsel, that required first getting some tools, and figuring out the right order to get those tools to operate different portions of the puzzle. I have watched sergeant major reef fishes learn how to wait for me to pop the lid off a rock oyster with a screw driver, so they could then dart in and grab the oyster.
Dang I had to pop the lids off three oysters, before they figured out the system, and started nudging my hand to “pop another one dude !”
Yeah, we moderns know how mammals should have done things.
Well tomorrow or Friday, we are going to get an earth shaking demonstration of just how stupid we really are.. That would be 11/20-21 /2014. That’s just over two weeks following an election. And the voters did NOT vote to commit National Hara Kiri.

Can anyone name for me a single important scientific discovery that has
(a) Benefited humanity in a non trivial way,
(b) Unlocked meaningful advance in understanding,
(c) Altered the paradigm of a field of science (in a positive way) and
(d) Come from computer modelling / simulation?
Just curious. (Maybe this will end up looking like a “what have the Romans ever done for us?” type of question.)

Well I wouldn’t exactly call Monte Carlo an “invention.”
All you are doing is taking some model of some system, and inserting valid values for all of the variables, and computing the result, and doing that for a large number of cases, and then doing statistics on the result. I do what is tantamount to MC all day long, simulating optical systems with models. They could be imaging (lenses) or non-imaging (as for illumination) and in the latter case, I might trace 100 million rays through a complex system of objects, which will produce showers of daughter rays, and then I plot where they go on suitable maps.
We used to do the same sort of job, particularly in imaging optics, by simply tracing (laboriously by hand with log tables) maybe three rays in two different colors, and then fine tuning the design from those three rays.
The trouble with tracing 10^8 rays, is that if you don’t get the result you want, the computer can’t tell you what the hell is wrong with your system, nor how to fix it. So in the end, you actually have to know optics.

Von Neumann and Ulam invented the process. What do you call their being the first to think up and use that statistical process? IMO, invention is the best word, but I’m open to suggestions for terms that better describe their achievement.
Ulam came up with the idea while playing solitaire during convalescence after severe illness, as the link describes.

So MC is simply statistical examination of the results of a large number of “experiments” which could be actual physical experiments, or computer simulations of a “good enough” model.
In manufacturing industries they have done that for eons in the QA testing of the manufactured output, to determine their “yield to spec.”
So doing it in simulation (MC) is simply doing what you already have been doing, with a computer model.
In the language of the patent office, that is something that is “obvious to one of ORDINARY skill in the art.”
Therefore it is NOT patentable, so not an invention.
The use of MC required the invention of computers; that WAS an invention. Using them on a task already being done is not an invention.
Von Neumann’s role in the origin of the computer is well known.

What types of inventions are not eligible for patent protection?
Some types of inventions will not qualify for a patent, no matter how interesting or important they are. For example, mathematical formulas, laws of nature, newly discovered substances that occur naturally in the world, and purely theoretical phenomena — for instance, a scientific principle like superconductivity — have long been considered unpatentable. In addition, the following categories of inventions don’t qualify for patents:
processes done entirely by human motor coordination, such as choreographed dance routines or a method for meditation
most protocols and methods used to perform surgery on humans
printed matter that has no unique physical shape or structure associated with it
unsafe new drugs
inventions useful only for illegal purposes, and
non-operable inventions, including “perpetual motion” machines (which are presumed to be non-operable because to operate they would have to violate certain bedrock scientific principles).

You’re probably correct on that. My short term memory has been shot for a while, and I’m not great with names anyhow.
But my mention of the computer, was simply to point out that MC computations are hardly practical without a computer, so the USE of MC methods HAD to wait till the invention of the computer. Doesn’t mean the idea did.
Space travel had to wait till suitable rockets were invented. The idea of space travel was known for eons before that.
But thanks for that Turing fix there.
G

An “invention” to be patentable, has to be novel (nobody else thought of it yet), useful (screen doors for submarines or ejection seats for helicopters, are not useful), and it has to be “non obvious to persons of ordinary skill in the art.”
So the test of obviousness is not for “experts” to whom everything (of course) is obvious.
And in the USA you typically have only one year to file for it, from the time of first disclosure, publication, or attempt to commercialize it (sell it). The new international patent law may have changed some of that. Now whoever files first gets the patent; so presumably you don’t have to invent. just stealing someone’s idea and beating him to the patent office works these days.
Makes for great co-operation between engineers and scientists.

Many many (too many) years ago, there was a short piece in an electronics industry magazine, in their “Ideas for Design.” column, about how you could use Monte Carlo analysis to determine manufacturing yields.
This engineer had designed a circuit and somebody had donated him an hour or so on some IBM mainframe (time shared) computer, so he thought he would do an MC analysis of his circuit.
Now his circuit was a two transistor amplifier, consisting of an emitter degenerated common emitter gain stage, followed by an emitter follower output stage.
He had done a WORST CASE DESIGN on this to ensure that this amplifier would have a voltage gain of 10.0 +/- 1.0 using 5% tolerance resistors for the design.
So his MC analysis set values for each of the resistors and transistor betas and the like, within the data sheet spreads, and 5% resistor tolerances he had used for his worst case design.
Now a worst case design always gets 100% yield to the spec, assuming live components, or else it is not a worst case design.
So he ran his Monte Carlo on his IBM freebie, and lo and behold, the computer told him that the midpoint gain was only 9.5 and not 10.0, and that moreover he could get gains that were outside the bounds of his worst case design.
The computer told him that the emitter degenerating resistor was the most critical component, and the collector resistor was second, and the first transistor beta was third most critical. It then told him to reduce the emitter resistor by about 5% and re run it.
Wow such artificial intelligence.
Unfortunately, the computer did not tell him: “Hey dude ! if you make the second stage an emitter coupled gain stage as well, and make those emitter resistors much smaller or zero, then you will get a whacking great gain of maybe 500 to 1,000, and then you can enclose the whole thing in a negative feedback loop, and set the gain to 10.0 with maybe a couple of 2% resistors, and then you can use 20% resistors for all the rest, and the transistor betas will have little or no effect.”
Well you see, computers and MC and statistics in general, can certainly tell you how lousy your circuit performs, but no computer can come up with a good design for you.
That’s why you learn circuit design in class, so that you can design circuits that are inherently good no matter what the computer thinks.
Statistics is good for telling you stuff you already know, because you have all the observed data, which is the most you can ever know about your experiment.
But statistics is good for convincing others that you know what you are doing; well what you have done, anyway.

Just curious. (Maybe this will end up looking like a “what have the Romans ever done for us?” type of question.)
Yep. Just consider the object you are reading these posts on and then think how similar discussions were carried on by Thomas Jefferson, or even Albert Einstein. We tend to cease crediting science once it has been converted to common place engineering.

Not sure you understood the question. I’m 100% for science and engineering. I was talking about attempts to recreate reality in complex computer simulations, and then describing the output of such simulation as a “discovery” about the real world, or as “data”. Climate science is the foremost exponent if this delusion.
You mention computers. Was their invention brought about by, err, computer simulation? This sounds like the Terminator storyline, where artificial intelligence time travels to reinvent itself.
If anyone invented computers it was Turing, not von Neumann. There was no simulation involved, just things like logic gates and digital memory.
I can think on one answer to mt question – Daisyworld by Jim Lovelock. This is a very simple conceptual modrl which unlocked a very important fact about the world and its biosphere. The biosphere regulates climate to its own advantage. This is a true advance in scientific understanding, not recognised by a climate research community too busy with fruitless computer gaming.

Don’t want to get in a trans-Atlantic priority match, but Neumann actually wrote his design for an electronic computer before Turing. More importantly, because of the thermonuclear bomb project, he actually got to build one.
But Great Britain can go us one better with Charles Babbage and Ada Lovelace, although of course the Analytical Engine was mechanical rather than electric.

Well, supply chain management for starters. Your chances of dropping into a major grocery store to find that they are out of canned peas for example is pretty low. Without computer models that track everything from this year’s crop, to current inventory levels by location versus consumption patterns tracked in realtime by location, and make predictions that are accurate enough for businesses to make supply chain decisions about, that just wouldn’t be possible, not to mention that the cost of the can of peas would be several times as high.
Actually, I would submit to you that you take for granted all sorts of things that are the results of computer modeling that meet your criteria. Drive a modern car? It has on board computer systems that model the physics of your car and based on the results of that model combined with realtime data input, make actual decisions ranging from turning on ABS to skid control and so on. Skyscrapers and highways are modeled first on computers, and many a bad design idea proven to be bad and so excluded from consideration. (That’s one of the nuances of modeling, it doesn’t necessarily produce a good idea as much as it facilitates the swift identification of bad ones). Same is true of everything from designing airplanes to nuclear power plants to mines. They are all major beneficiaries of computer modeling that in fact are non trivial, unlock meaningful (applicable) understanding, and altered many a paradigm.
We discuss so much of the misuse of computer models on this site that I think we sometimes lose site of the fact that the positive aspects of modeling are all around us in the things that we take for granted. It is like asking if guns are good or bad. Guns have neither morals nor ethics, they are neither good nor bad. What they get used for, that’s a different question.

Einstein built mathematical models (i.e., sets of equations) of the implications of his theory of General Relativity and the universe. But at least he had the intelligence not to believe their results until the empirical evidence came, in decades later. He really though his math was wrong (or not applicable to reality) in many cases (e.g., black holes).

Davis said. “We have concerns about the precision of the modeling techniques now being used. We don’t have any concerns about climate change happening and that it going to cause geographic range shifts for mammals and plants. The thing I want to do, as a scientist, is to have the best models possible so as we’re making informed decisions as a society.”
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When did society become a scientists concern ?

Mammals didn’t play by the rules of modeling on where they migrated to survive last ice age, says UO researcher
Given that the climate models are seriously deficient in terms of regional climate change, they may have simply modeled a climate change that didn’t occur, and that is why the flora and fauna existed where the climate models said they shouldn’t be. Strikes me as odd that they went to the trouble of comparing the existence of fossil shrews to an area and not bothering to seek evidence of climate change from that area in other proxies rather than relying exclusively on climate models (or at least doing some proxy evaluation to confirm the models output)

Animals do learn.
Difficult to tell even today with living specimens how much is instinct and how much learning, and there’s the possibility that rogue genetic changes get rewarded with greater reproduction as conditions change.
A fish expert used the term “adaptive behavior” in a discussion about herring, which aren’t as smart as animals.
My favourite example is Gray whales, who only feed in the Bering Sea. Some years ice clogs it, which is bad for survival of nursing females, they head north with calf, having not eaten since last summer. The species will survive, as some mavericks feed off the BC coast (about 1% of total in eastern Pacific) and about 10% skip the commute and stay off the OR coast).

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